Healthcare big data draws lessons from 'Moneyball' stats

At the Healthcare IT News Big Data & Healthcare Analytics Forum on Thursday, one CMIO showed how healthcare data mining and baseball Sabermetrics have more in common than one might think. Both want to notch some big wins.

His argument – hard to argue with – is that population health management has to be an evidence-based team sport.

Baseball and healthcare have some things in common. For many years, both often operated on an established set of rules and handed-down wisdom -- sometimes even going on hunches and gut feelings -- until some folks started asking whether it might be worth rethinking some basic tenets, making better use of available data to do things more effectively and efficiently.

In Moneyball, Oakland A's general manager Billy Beane famously turned to shrewd numbers crunching to find undervalued players, fielding successful teams with a payroll the fraction of the size of its American League competitors.

The same is happeng in healthcare. And not a moment too soon, as costs continue to climb, quality of care often remains middling and chronic diseases are imperiling whole populations: "Diabetes is the new cancer in the United States," said Kudler.

Thanfully, the data is there to offer insights into how things could be better, and drive real changes in how population health is managed: "If data isn't intuitively actionable, it's just an academic adventure," he said.

Kudler's novel approach is to frame pop health like a baseball box score. In his equation, anticipating and remediating risk represented a team's offense; adjustments to its care management strategies are its defense. (Healthcare providers are the players here; patients are fans.)